Stock price analysis based on the research of multiple linear regression macroeconomic variables
Fei Wang, Wanling Chen, Bahjat Fakieh, Basel J. A. Ali
Abstract
Abstract The article uses SPSS statistical analysis software to establish a multiple linear regression model of short-term stock price changes of domestic agricultural listed companies. The article uses a stable time series based on the ARMA model for stable agricultural value-added, fiscal expenditure and market interest rates. The regression method is used to study its impact on the stock price index. Compared with the existing stock forecasting methods, this method has simple data collection and no specific requirements for data selection, and the prediction results have a high degree of fit. Therefore, this method is suitable for most stocks.
Topics & Concepts
EconometricsRegression analysisStock (firearms)Simple linear regressionLinear regressionEconomicsStock priceStock marketTime seriesRegressionStock market indexStatisticsComputer scienceMathematicsSeries (stratigraphy)EngineeringGeographyArchaeologyPaleontologyMechanical engineeringContext (archaeology)BiologyEnergy Load and Power ForecastingEnergy, Environment, Economic GrowthMarket Dynamics and Volatility